Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add xberg-io/liter-llm --skill running-the-proxygit clone --depth 1 https://github.com/xberg-io/liter-llmWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/xberg-io/liter-llm/running-the-proxy)<a href="https://agentmods.dev/skills/xberg-io/liter-llm/running-the-proxy"><img src="https://agentmods.dev/badge/skills/xberg-io/liter-llm/running-the-proxy/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xberg-io/liter-llm/running-the-proxy"><img src="https://agentmods.dev/badge/skills/xberg-io/liter-llm/running-the-proxy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 55 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium MCP Rug Pull · line 67 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.00543 |
| Opus 5 | $0.00025 | $0.00271 |
| Sonnet 5 | $0.00010 | $0.00109 |
| Haiku 4.5 | $0.00005 | $0.00054 |
Grade A, and why
running-the-proxy scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl http://localhost:4000/v1/chat/completions \ What it actually says
Running the Proxy
liter-llm api is a drop-in OpenAI-compatible gateway: 22 REST endpoints that
route to 165 providers, with multi-tenant virtual keys, rate limits, budgets,
and cost tracking.
Start it
liter-llm api --config liter-llm-proxy.toml
The proxy auto-discovers liter-llm-proxy.toml in the current directory.
Configuration
[server]
host = "0.0.0.0"
port = 4000
[general]
master_key = "${LITER_LLM_MASTER_KEY}"
# Each [[models]] entry maps a routable name to a provider/model and its key.
[[models]]
name = "gpt-4o"
provider_model = "openai/gpt-4o"
api_key = "${OPENAI_API_KEY}"
[[models]]
name = "claude-sonnet"
provider_model = "anthropic/claude-sonnet-4-20250514"
api_key = "${ANTHROPIC_API_KEY}"
# Virtual keys scope which configured model names a caller may use.
[[keys]]
key = "sk-team-frontend"
models = ["gpt-4o", "claude-sonnet"]
rpm = 60
tpm = 100000
budget_limit = 50.0
${ENV_VAR} interpolation keeps secrets out of the file.
Call it like OpenAI
curl http://localhost:4000/v1/chat/completions \
-H "Authorization: Bearer sk-team-frontend" \
-d '{"model": "gpt-4o", "messages": [{"role": "user", "content": "Hello"}]}'
Notes
- Virtual keys scope which models a caller may use and carry their own RPM/TPM
and budget limits; the
master_keyadministers them. - The OpenAPI 3.1 spec is served at
/openapi.json. - Endpoints cover chat, embeddings, images, audio, moderations, files, batches, responses, and model listing.
- Docker:
docker run -p 4000:4000 -e LITER_LLM_MASTER_KEY=sk-key ghcr.io/xberg-io/liter-llm.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 68 lines · 50 tokens per session scan A 1b8d61b0814d
running-the-proxy is a skill published in the GitHub repository xberg-io/liter-llm (252 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 543 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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